www.iied.org 1 IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017 Irish Aid Climate and Development Learning Platform Zambia Case Study Final Report Climate Resilient Agriculture in Northern Province, Zambia: Integrating Considerations of Climate into Cropping Strategies of Smallholder Farmers Sam Barrett and Durton Nanja
39
Embed
Irish Aid Climate and Development Learning Platform · irish aid learning platform – zambia final report – august 2017 agriculture and met departments), and an interest in such
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
www.iied.org 1
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Irish Aid Climate and Development
Learning Platform
Zambia Case Study Final Report
Climate Resilient Agriculture in Northern Province,
Zambia: Integrating Considerations of Climate into
Cropping Strategies of Smallholder Farmers
Sam Barrett and Durton Nanja
www.iied.org 2
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Contents
Executive Summary 3
Introduction 4
Literature Review 5
Developing Resilient Cropping Strategies with Climate Risk Assessment and Seasonal Forecast 9
Integrating Climate Risk Assessments and Seasonal Forecasts 14
Findings 18
Challenges and Next Steps 22
References 23
Appendix A 27
Appendix B 31
Appendix C 34
www.iied.org 3
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Executive Summary Agriculture remains the productive base for rural communities in Least Developed Countries
(LDCs) and Lower-Middle Income Countries (LMIC) in Sub-Saharan Africa. Zambia’s
population remains predominantly rural and agriculture based, and thus has acute exposure
and sensitivity to climate variability and change. High inter-annual rainfall variability,
especially in relation to onset and cessation, are weighing on the development of smallholder
farmers, and contributing to vulnerability and food insecurity.
The Irish Aid Climate Change and Development Learning Platform seeks to improve resilience
through climate risk management in development programming. In the case reported here this
was attempted through institutional and farmer learning on climate risk management
mainstreaming. This case study for the Zambian Mission facilitated experiential learning on
climate risks faced by farmers and the support institutions in current development activities in
Northern Province. The investigation uses existing farmer demonstration plots operated by
Livelihood Enhancement Groups (LEGs), together with engagement from partners (Self-Help
Africa and CGIAR consortium), to adjust business-as-usual cropping strategies for climate
risk.
This final report details the stages of the exercise carried out between February 2016 and July
The case study combines knowledge from climate risk assessments, seasonal forecast
information, with participatory techniques. The objective is for LEG participants and their
supporting institutions to learn about climate risks smallholder farmers experience in Mbala
Information + Knowledge
- Climate Events
- Climate Trends
- Climate Forecasts - Climate Projections
- Local Climate Experience
Climate Resilient
Decision-Making
Capacity Assumption
Incentive Assumption
Reduce Losses
Benefits from Opportunities
Enabling Environment
www.iied.org 9
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
and Lwingu districts, and assist them in applying this knowledge of risks and climate
information to make decisions that improve climate risk management and climate resilience.
Developing Resilient Cropping Strategies with
Climate Risk Assessment and Seasonal Forecast This section outlines the design and application of the climate risk assessment. The first sub-
section sets out aims and objectives. The second sub-section outlines the 3 step approach.
The third sub-section explains the methodological application of the risk assessment and
seasonal forecast to make decisions on cropping strategies. The fourth sub-section
documents the findings.
Aims and Objectives
The objective is to design a participatory climate risk assessment tailored to inform the climate
farmer field school in Mbala and Luwingu districts. What follows is adapted from Willows et al.
(2003) and Ozor and Cynthia (2011) (see Figure 2) and frames climate risk in terms of
hazards multiplied by crop losses. The assessment identifies specific climate risks of different
crops by accounting for: a) hazards thresholds for crops; b) effects of hazards on crops
(sensitivity component of vulnerability); and c) the current ability to adapt and associated
success (representing adaptive capacity).
Figure 2: Climate Risk Assessment Adapted to inform Climate Farmer Field School
: Crop Yield
!
: Crop Yield
!
Hazards
- Erratic Rainfall
- Drought
- Flood
- Storms
Current
Ability to
Adapt
Effect on Crops
- Crop Failure
- Low Yield
- Diseases
- Low Soil Fertility
Yes
- Mulching
- Seed Varieties
- Pesticides
No
- Limited Resources
- Poor Physical Health
- No crop alternatives
Fully
Address
Risk
Yes
No
Coping Range
Climate Risk
www.iied.org 10
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
3 Step Approach
Step 1: Identify and define the nature and extent of the exposure units, receptors, and
assessment period;
LEGs are the units of interest, made up of participating members. LEGs will aggregate climate
risks of each participating member into the design and implementation of experiential learning
plots (see Appendix A for survey design for households). Therefore, the climate risk to
farming activity of participating LEG members will be assessed in terms of crop production,
and reinforced by LEG focus group discussions. Finally, the assessment period will be the
last five cropping seasons, and so the past five years.
Step 2: Identify climate variables to which the exposure unit is sensitive and able/unable to
adapt.
LEGs participants in Luwingu and Mbala will be surveyed on their experience with erratic
rainfall, shorter seasonal rains, drought, dry spells and temperature rise (Smith, 2015). To
understand sensitivity, assessors will: a) first document climate variables considered a hazard
by each household; b) establish the ‘coping range’ for each crop type, in terms of identifying
thresholds where crop production is adversely affected. The process of recording the range of
values for climate variables (e.g. number of consecutive wet days per season, maximum
temperature) in which crops are viable/not viable reveals socio-economic vulnerability of the
farming system.
To understand adaptive capacity, the climate risk assessors will: a) document the
presence/absence of adaptation/resilience measures designed to adapt to climate stresses on
crops; b) if such measures are in place, gauge the degree of effectiveness in reducing risk.
For example, too much rain can saturate maize crops, and raising the planting mound allows
for tolerance of heavy rainfall. The important aspect is document how much rain such
technologies can withstand; alternatively, to address shorter wet seasons, farmers may switch
to early maturing varieties to circumnavigate this hazard. Again, precisely how short can a
season become and a crop experiences no adverse effects. This facilitates an understanding
of coping ranges for different crops.
Figure 3 illustrates climate variability for a single crop. The grey area is the coping range in
the years before and at the time of the assessment, which simultaneously represents the
extent of climate sensitivity and adaptive capacity of farmers. The blue area incorporates the
projection data of the climate variable, and necessary changes to sensitivity and adaptive
capacity needed to address emerging climate change.
www.iied.org 11
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Figure 3: Example of Climate Variable (e.g. rainfall level) and Coping Range
Adapted from Willows et al. (2003)
Step 3: Using climate-scenarios and risk assessment to determine climate risk. Based on adverse climate impacts on crops in recent seasons, the objective is to aggregate
knowledge on the extent and nature of the climate risks to crops likely over the season. The
second objective is to establish the likelihood of experiencing climate hazards over the same
time period. This identifies changes in climate risk over time that are relevant to farming
systems in Mbala and Luwingu as the primary output of the climate risk assessment:
identifying the present and immediate future climate risk to different crops, given
current levels of sensitivity and adaptive capacity.
Decision-Making Methodology
The development of a climate risk management strategy for crops is highly contextual,
requiring systematic integration of knowledge from the climate risk assessment, combined
with climate information. The experience of smallholders and extension teams are already
embedded within current strategies – including on-going adaptive measures – and the
purpose of the climate farmer field school is for all LEG participants, SHA and other partners
to assimilate their understanding of climate risk and uncertainty within each of the 4 LEGs.
The first step is to calculate climate risk using the following formula: risk = probability of
hazard occurrence x magnitude of loss. Figure 4 shows that the probability of a hazard
occurring in any year is the likelihood that normal variability in weather/climate gives way to
hazardous conditions, and has adverse effects on crops. The magnitude of the loss
represents the scale of the impact. For instance, this can be measured either in yield losses
Climate-Smart
Decision-Making
Reduce Losses
Capacity
Assumption
Clim
ate Variab
le
Critical Threshold CR1
Present Past Future
Below critical threshold represents the level of climate variability that the LEGs can respond to given past, present
and future sensitivity and adaptive capacity, and provide a coping range given the soci-economic characteristics of the
individual farmers; above the critical threshold requires a change in the sensitivity and adaptive capacity to reduce
climate risk, and improvements corresponding increases socio-economic characteristics
Coping Range = Sensitivity + Adaptive Capacity
Critical Threshold CR2
www.iied.org 12
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
(e.g. Kg), the monetary value of yield losses (e.g. some currency value) or another standard
metric. Figure 4 shows that if you have a 0.34 probability of a hazardous weather/climate
event occurring within any one year, and with $50 loss typically associated with such an event,
climate risk for that crop is $85, assuming a 5 year reference period. This value can be
compared to those for other crops so as to inform decision-making under climate uncertainty.
Figure 4: Calculating Climate Risk Using Climate Knowledge and Information
Figure 5 outlines the knowledge and information components that together constitute the
likelihood of hazard occurrence. Knowledge from the climate risk assessment indicates the
thresholds where weather/climate variability becomes hazardous for particular crops within the
context, and the effectiveness of adaptive measures in raising this threshold. Information is
both short- and long-term, but is subject to availability. Short-term information (rainfall only) is
available through the use of seasonal forecasts, which provide probabilistic signals for rainfall
outcomes in the approaching season, and which further inform the likelihood of breaching
crop-hazard thresholds identified during the climate risk assessment. Long-term information
indicates systemic changes in rainfall and temperature over years.
The systematic integration of climate information with findings of the risk assessment is a
challenge. Using the formula (risk = probability of occurrence x the magnitude of the hazard),
the objective is to adjust the probability of occurrence (initially calculated from daily rainfall
data) according to climate information that suggest a change in the likelihood of hazard
occurrence previously identified in the risk assessment. For the seasonal forecast, standard
calculations of probability of occurrence are adjusted by observing the likelihood of the same
hazard occurring in years when forecasts are normal, below or above normal. For instance,
the standard probability may be 0.35 for a 15 days dry spell in any one year, but in an above
normal year, the same hazard may occur only once in 5 years (0.20). Therefore, the
probability a 15 day threshold being breached in an above normal year will be 0.27 (0.35 +
0.20 / 2 = 0.27).
Climate Risk
= $85
Prob. Of Hazard
Occurrence (1Yr)
x
Average
Magnitude of Crop
Losses
Calculate Avg.
Losses (5 Years)
0.34 x $50 (x5)
Historical Knowledge
of Climate Risk
1. Identify crop-hazard
interactions and
respective thresholds;
2. Using frequency of
crop-hazard interactions
in recent years, calculate
the probability of
occurrence in any one
year.
Seasonal Forecast
1. Use probabilistic
seasonal forecast to
estimate likelihood of
breaching threshold;
2. Calculate likelihood
of crossing threshold
where variability
becomes hazardous for
crop
!
Climate Projections
1. Use longer-term
likely future trends in
temperature and rainfall
2. Calculate incremental
changes in future
temperature and rainfall
!
!
www.iied.org 13
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Figure 5: Using Climate Risk Calculation to Re-Configure Experiential Learning Plot from Business-as Usual Scenario
The second step operationalizes calculations to inform decision-making for the climate risk
management strategy. Figure 6 demonstrates the method used in the design of experiential
learning plots. The objective is to calculate proportions within the treatment section of the plot
given each crop type, which minimises losses and maximise benefits, whilst also considering
and building on the original cropping preferences of farmers. Using the probabilities of hazard
occurrences in combination with the magnitude of losses provides a basis on which to make
systematic comparisons across crop types, and which serves as the basis to make space
allocations. The final stage is to compare values of likely losses with the original proportions
allocated to crops in the business-as-usual scenario, and make upward/downward
adjustments to the proportion of each crop in the treatment plot.
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Shimumbi: the major treatment crop after negotiations and planting was cassava at 39.9% (an
increase from 25.3% in the business as usual scenario). This cassava crop performed
exceptionally poorly, with the harvest representing only 62K (8.8% of treatment plot value).
Maize was reduced from 32.1% to 26.8%, but represented 55.5% of yield value (388 K).
Groundnuts were also reduced from 17.4% to 12.2% of land used, but which out-performed by
yielding 25.1% of total value. Once again, too much emphasis was given to cassava in this
one season, when the weather conditions (786mm) favoured maize and groundnuts.
Chozi: the major treatment crop after negotiations and planting was maize at 50.3% (an
increase from 33% in the business as usual scenario). This maize crop out-performed the rest
of the crops, through the 491 K generated representing 82% of total value for the treatment.
While groundnuts were planted in 25.2% of the plot (up from 14.3% in the business as usual
scenario), the 45 K generated only accounted for 7.5% of the total. Beans were reduced from
16.5% in the business as usual scenario, to 8.4%. This was a correct move overall, because
the entire beans crop failed. Millet was a new crop brought in via the negotiations (10.4% of
treatment land used), but which significantly under-performed (15 K) by only contributing 2.5%
of the treatment value. Overall, a heavier emphasis on maize was the most important
determinant in the treatment performing better than the control.
In summation, the treatments performed well when the focus on maize was maintained, and
they performed poorly when cassava replaced maize. But cassava is the insurance against
exceptionally dry seasons, which didn’t materialise this season. The risk assessment signified
that a disproportionate share of the risk was often attributable to maize, and to a lesser extent,
groundnuts. To repeat from above, climate related losses to maize are typically associated
with drier years, and the seasonal rainfall this season appeared to be sufficient in the areas of
the LEGs. Therefore, to understand the performance of adjusting for climate risk, it will be
necessary to evaluate the method used as an iterative process. The objective is for the
methodology to enable farmers to perform better across all seasons, despite the likely
increase in between year variability in rainfall.
www.iied.org 22
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Challenges and Next Steps As a case study commissioned by the Irish Aid Climate Change and Development Learning
Platform, the establishment of climate resilient cropping strategies with the pre-existing LEG
system was first and foremost designed to be a learning process. Therefore, the crop yield
results are secondary, and the engagement and shared learning with the LEG farmers and
support institutions was of paramount importance. More specifically, the original concept
note envisaged that personnel in the support institutions would learn most from the exercise
and then transfer knowledge on to smallholder farmers over time through recurrent
engagement.
This emphasis on learning and knowledge transfer means that the engagement by support
institutions has to be high quality and constant. In this case, good early interest in the process
dwindled over time.
Another challenge in this first year of the process was that the controls were not planted as
had been planned. Instead, just the treatments were planted at the start of the season. All
yield calculations of the control had to be developed from yield and area measurements of the
treatment, and that of surrounding farms. This reduced the experiential smallholder farmer-
learning component of the study. Additionally, instead of including the various different
practices in the treatments and comparing these with the business-as-usual scenario in the
control, the comparisons were just the changes in space allocations to crops. Changes in
seed varieties, adaptation measures, such as ridging, using climate information to gauge
planting time, and many other techniques discussed to circumnavigate climate hazards were
not implemented as planned.
Next Steps
Much has been learnt from the trialling the approach in Northern Province. The case study
was designed to be an iterative process, spanning multiple seasons and with consistent
engagement from a committed team of participants keen to learn about addressing threats to
cropping for smallholder farmers, particularly from variation in rainfall. To achieve this Irish
Aid will need to work with agencies with more permanent mandates to smallholder farmer
development. This might include providing resources to engage local government (particularly
agriculture and met departments) directly in a collaborative team interested in the work as a
medium term learning exercise. The institutional learning is key, but knowledge should passed
on to smallholder farmers, who as the most vulnerable to emerging climate change, should
always be the main focus of such exercises.
The case study in Northern Province put into practice an approach set out in the new Irish Aid
technical note on climate resilient agriculture. As such, and as a means for Irish Aid to
meeting institutional objectives of food security, vulnerability reduction, climate and
development, the process of adjusting on-going development activity to climate risk will offer a
guide to all future partner engagement relating to agriculture. Therefore, lessons learnt will be
communicated around the Irish Aid Missions to ensure development programming for
smallholder farming improves as a result of the case study, and any future uptake of the
approach to climate resilient cropping can avail of past experiences.
www.iied.org 23
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
References Adger, W.N., Brown, K., and Waters, J. (2011). Resilience. in: Dryzek, J., Norgaard, R., and Schlosberg, D. (eds.), Oxford Handbook of Climate Change and Society, Oxford University Press, Oxford, 696-710. Aldunce, P., Beilin, R., Handmer, J., &Howden, M. (2014). Framing disaster resilience: The implications of the diverse conceptualisations of “bouncing back”. Disaster Prevention and Management 23, 252-270. Am, P., Cuccillato, E., Nkem, J., Chevillard, J. (2013). Mainstreaming climate change resilience into development planning in Cambodia. IIED Country Report, 1-12. Anderson, S. (2011). Assessing the effectiveness of climate adaptation. IIED Opinion, 1-2. Ayers, J., & Huq, S. (2009). Supporting adaptation to climate change: what role for official development assistance? Development Policy Review 27, 675-692. Barrios, S., Bertinelli, L., & Strobl, E. (2010). Trends in rainfall and economic growth in Africa: A neglected cause of the African growth tragedy. The Review of Economics and Statistics 92, 350-366. Boer, R., Tamkani, K. & Subbiah, A. (2014). Communicating climate forecast to farmers through climate farmer field school: The Indonesia experience. Unpublished Report, 1-7. Bosello, F., Eboli, F., & Pierfederici, R. (2012). Assessing the economic impacts of climate change. FEEM (FondazioneEni Enrico Mattei), Review of Environment, Energy and Economics (Re3). Braun, A., & Duveskog, D. (2011). The farmer field school approach: History, global assessment and success stories. Background paper for the IFAD Rural poverty report. 1-39. Chiliufya, W. (2017). Fall army worm maize attack: a case for diversity from farm to fork. IIED Blog - https://www.iied.org/fall-army-worm-maize-attack-case-for-diversity-farm-fork Christian Aid. (2009). Developing a climate change analysis, in IIED (eds) Participatory Learning and Action: Community-Based Adaptation to Climate Change, IIED Publication. Cook, S and Boerwinkel, F. (2017). Promoting diversity on the farm – and the plate. IIED Blog - https://www.iied.org/promoting-diversity-farm-plate Daze, A., Ambrose, K. and Ehrhart, C., (2009). Climate vulnerability and capacity analysis handbook. Care International, 1-52.
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
FAO (2010) Facilitators’ Guide for Running a Farmer Field School: An adaptation for a post emergency recovery programme. Folke, Carl. (2006). Resilience: The emergence of a perspective for social–ecological systems analyses. Global Environmental Change 16, 253-267. Folke, C., Carpenter, S., Elmqvist, T., Gunderson, L., Holling, C.S. and Walker, B., (2002). Resilience and sustainable development: building adaptive capacity in a world of transformations. AMBIO: Journal of the Human Environment 31, 437-440. Government of Ireland. (2013). One World, One Future: Ireland’s Policy for International Development. Government Publications, 1-44. Government of Zambia (GoZ). (2010). National Climate Change Response Strategy. Ministry of Tourism, Environment and Natural Reources. 1-135. Government of Zambia (GoZ). (2010). National Policy on Climate Change. Ministry of National Development Planning. 1-20. Government of Zambia (GoZ). (2015). Intended Nationally Determined Contributions. UNFCCC Document. 1-12. Government of Zambia (GoZ). (2015). Intended Nationally Determined Contributions. UNFCCC Document. 1-12. Intergovernmental Panel on Climate Change (IPCC). (2001).Climate Change 2001: Synthesis Report. Cambridge University Press, Cambridge. Intergovernmental Panel on Climate Change (IPCC). 2014: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Barros, V.R., C.B. Field, D.J. Dokken, M.D. Mastrandrea, K.J. Mach, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 688. International Institute for Sustainable Development (IISD). (2012). Community-Based Risk Screening Tool: Adaptation and Livelihoods. CRiSTAL Users Manual, 1-56. Irish Aid. 2016. Building Resilience. Irish Aid Policy Brief. 1-21. Irish Aid. 2017. Climate Resilient Agriculture in Smallholder Farming: Issues for Development Programming. Irish Aid Policy Briefing, 1-14. Irish Aid. 2017a. Climate Resilient Agriculture in Smallholder Farming: Issues for Development Programming. Irish Aid Technical Note, 1-20.
www.iied.org 25
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Jones, Xiaoting Hou and Franks, Phil, (2017). Shaping the future of forest and farm landscapes in Africa. IIED Blog - https://www.iied.org/shaping-future-forest-farm-landscapes-africa
Jones, R. and Preston, B. (2010). Adaptation and risk management. Climate Change Working Paper No. 15, Centre for Strategic Economic Studies, Melbourne, 1-18. Patt, A., Suarez, P. and Gwata, C., (2005). Effects of seasonal climate forecasts and participatory workshops among subsistence farmers in Zimbabwe. Proceedings of the National Academy of Sciences of the United States of America 102, 2623-12628. Plambeck, E. L., & Hope, C. (1996). PAGE95: An updated valuation of the impacts of global warming. Energy Policy 24, 783-793. New Economics Foundation (NEF). (2013) Counting on uncertainty: The economic case for community-based adaptation in North-Eastern Kenya. New Economics Foundation, 1-48. Ozor, N. and Cynthia, N., (2011) The role of extension in agricultural adaptation to climate change in Enugu State, Nigeria. Journal of Agricultural Extension and Rural Development 3, 42-50. Rockefeller Foundation. 2009. Building Climate Change Resilience. Rockefeller Foundation, New York. Siregar, P. and Crane, T. (2011) Climate information and agricultural practice in adaptation to climate variability: the case of climate field schools in Indramayu, Indonesia. Culture, Agriculture, Food and Environment 33, 55-69. Sonwa, D., Dieye, A., El Mzouri, E., Majule, A., Mugabe, F., Omolo, N., Wouapi, H., Obando, J. and Brooks, N. (2016). Drivers of climate risk in African agriculture. Climate and Development, pp.1-16. Smith, B. (2015). Climate change in Northern Zambia: Implications for Irish Aid Programmes. IIED Consultancy Report, 1-15. SUSTAINET EA (2010). Technical Manual for farmers and Field Extension Service Providers: Farmer Field School Approach. Sustainable Agriculture Information Initiative, Nairobi. Tadross, M., Hewitson, B. and Usman, M (2005).The interannual variability of the onset of the maize growing season over South Africa and Zimbabwe.Journal of climate 8, 3356-3372. Tadros et.al, (2008) Regional expert meeting: “Changes in growing-season rainfall characteristics and downscaled scenarios of change over southern Africa: implications for growing maize” Meeting Report. Travis, W. and Bates, B. (2014) What is climate risk management? Climate Risk Management 1, 1-4.
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
USAID. (2014) Climate-resilient development: A framework for understanding and addressing climate change. USAID, Washington DC. Van Aalst, M., Helmer, M., de Jong, C., Monasso, F., van Sluis, E. and Suarez, P., (2007) Red Cross/Red Crescent Climate Guide. Technical Rep., Red Cross/Red Crescent Climate Centre Publication, 1-73. Wiggins, M. (2009) CEDRA: Climate change and environmental degradation risk and adaptation assessment. Teddington, UK: Tearfund, Willows, R., Reynard, N., Meadowcroft, I. and Connell, R., (2003) Climate adaptation: Risk, uncertainty and decision-making. UKCIP Technical Report. UK Climate Impacts Programme, 70-89. Wisner, B., Cannon, T., Davies, I., Blaikie, P. (2004)At Risk: Natural Hazards, People’s Vulnerability and Disasters. Routledge, London. World Bank. 2017. Zambia Strengthening Climate Resilience (PPCR Phase II) (P127254). Implementation Status & Results Report, 1-22.
www.iied.org 27
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Appendix A
www.iied.org 28
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Zone Name: Interviewee’s Name:
LEG Number:
HOUSEHOLD DEMOGRAPHY
a) Male/Female Headed Household (M/F)
b) Number of Adult Men ( ) and Women ( )
c) Number of Children ( )
d) Age and Education of Adults:
Age Education in Years
Adult 1 ( ) ( )
Adult 2 ( ) ( )
Adult 3 ( ) ( )
Adult 4 ( ) ( )
Adult 5 ( ) ( )
Adult 6 ( ) ( )
Adult 7 ( ) ( )
Adult 8 ( ) ( )
TYPICAL CROP STRATEGY
Crop Type Specifications Proportion
1. ( ) ( ) ( % )
2. ( ) ( ) ( % )
3. ( ) ( ) ( % )
4. ( ) ( ) ( % )
5. ( ) ( ) ( % )
6. ( ) ( ) ( % )
7. ( ) ( ) ( % )
Total ( % )
CROP-RELATED CLIMATE HAZARDS AND SENSITIVITY (PER CROP-HAZARD)
Type Crop/Variety Threshold* Prop Lost Value
2015 ( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
* mm, days, oC, hale, wind speed (kph)
www.iied.org 29
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Type Crop/Variety Threshold* Prop Lost Value
2014 ( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
2013 ( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
2012 ( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
2011 ( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
( ) ( ) ( ) ( %) ( Kwa)
* mm, days, oC, hale, wind speed (kph)
REFLECTION ON MAIN CLIMATE HAZARDS AND SENSITIVITY
Please reflect on the main climate hazards affecting your crop-based livelihood activities (Record All
Points)
www.iied.org 30
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
MAIN ADAPTIVE MEASURES TO ADDRESS CROP-RELATED HAZARDS
Hazard-Crop Interaction Adaptive Measure
1. ( ) ( )
Change in Threshold From ( ) To ( )
Hazard-Crop Interaction Adaptive Measure
2. ( ) ( )
Change in Threshold From ( ) To ( )
Hazard-Crop Interaction Adaptive Measure
3. ( ) ( )
Change in Threshold From ( ) To ( )
Hazard-Crop Interaction Adaptive Measure
4. ( ) ( )
Change in Threshold From ( ) To ( )
Hazard-Crop Interaction Adaptive Measure
5. ( ) ( )
Change in Threshold From ( ) To ( )
* mm, days, oC, hale, wind speed (kph)
www.iied.org 31
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Appendix B
REFLECTION ON MAIN CLIMATE HAZARDS AND ADAPTIVE CAPACITY
Please reflect on the measures used to address your main climate hazards, and their effectiveness in
lowering your risk (Record All Points)
www.iied.org 32
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Zone Name/LEG Number:
Focus Group Type: Women / Youth / Men
TYPICAL CROP STRATEGY
Crop Type Specifications Proportion of Strategy
1. ( ) ( ) ( )
2. ( ) ( ) ( )
3. ( ) ( ) ( )
4. ( ) ( ) ( )
5. ( ) ( ) ( )
6. ( ) ( ) ( )
7. ( ) ( ) ( )
8. ( ) ( ) ( )
9. ( ) ( ) ( )
10. ( ) ( ) ( )
CROP-RELATED CLIMATE HAZARDS AND SENSITIVITY
Describe and reflect on the type of crops commonly used, the hazardous climate effects, the specific
level or threshold where the climate becomes hazardous, and describe the adverse impact on crops.
www.iied.org 33
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
REFLECTION ON MAIN CLIMATE HAZARDS AND SENSITIVITY
What is the single most significant threat to any one crop from climate related hazards?
CROP-RELATED HAZARDS AND ADAPTIVE CAPACITY
Please describe measures used to adapt to each hazard for each crop. How effective is each
adaptive measure in reducing the threat from the climate hazard?
www.iied.org 34
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Appendix C
www.iied.org 35
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Figure 8: Diagrams of Experiential Learning Plot for Mfungwe LEG. From Top-Left in Clockwise Direction, Risk Adjusted, Negotiated, Planted and Yield of LEG
Treatments versus Business as Usual (Original Cropping Strategy)
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Figure 9: Diagrams of Experiential Learning Plot for Zombe LEG. From Top-Left in Clockwise Direction, Risk Adjusted, Negotiated, Planted and Yield of LEG
Treatments versus Business as Usual (Original Cropping Strategy)
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Figure 10: Diagrams of Experiential Learning Plot for Shimumbi LEG. From Top-Left in Clockwise Direction, Risk Adjusted, Negotiated, Planted and Yield of
LEG Treatments versus Business as Usual (Original Cropping Strategy)
IRISH AID LEARNING PLATFORM – ZAMBIA FINAL REPORT – AUGUST 2017
Figure 11: Diagrams of Experiential Learning Plot for Chozi LEG. From Top-Left in Clockwise Direction, Risk Adjusted, Negotiated, Planted and Yield of LEG
Treatments versus Business as Usual (Original Cropping Strategy)